Swarm-Lite — Project Studio

The problem

Product teams are reactive by default. They gather user feedback late, expensively, and at the wrong moment.

When a new feature is proposed internally, the question “what would our users think?” triggers a research process that takes weeks to complete — by which time the feature has already been scoped, estimated, and committed to a sprint. When a positioning change is debated in a leadership meeting, no one in the room represents the voice of the customer.

Swarm-Lite removes that cost entirely. It answers the question in minutes, before the decision is already made.

The concept

A Project Manifest defines your product, your target market, and the archetypes of the users you are building for. Swarm-Lite generates a swarm of AI personas — each with a defined role, seniority level, domain expertise, and known pain points — and allows you to run Huddle sessions: structured conversations where the swarm evaluates a feature, a positioning decision, or a strategic change.

The output is a Huddle Summary: per-persona sentiment, specific objections and conditions, a composite recommendation, and a set of Pending Actions for the user to approve or dismiss. The swarm does not make the decision. It surfaces the reasoning behind likely reactions. The human owns the conclusion.

Architectural decisions

Markets, Personas, and Projects as three distinct entities

Not a flat feed. Not a single ‘project’ object that contains everything. Three separate entities that can be composed. A persona exists independently of any market or project. A CTO archetype created for one product is immediately available for another. A market definition — with its tracked competitors, conditions, and signals — is a reusable asset that multiple projects can reference.

Session branching — non-destructive thread forking

Different stakeholders want to interrogate the same scenario from different angles. A Create Session Branch allows any of these questions to be asked as an isolated thread without contaminating the main session record. The original Huddle remains unchanged. The branch produces its own summary. Both are saved, both are auditable, and neither overwrites the other.

HITL approval on Pending Actions

Same pattern as TX-1 and SS-1. The agent proposes. The human approves. Pending Actions are the interface between agent reasoning and human decision-making. An agentic system that acts without asking is noise. An agentic system that asks for approval on every trivial step is friction. The Pending Actions model is the product design decision that determines where the line sits.

Per-persona sentiment over aggregate score

The Huddle Summary shows each persona’s response individually. An averaged sentiment score of 3.8/5 looks like “broadly positive.” But the underlying data is: two strongly positive, one conditional, one mixed. The conditional and mixed responses contain the most valuable signal — the specific objections, the pricing concerns, the security requirements — and they are invisible in an aggregate.

The Huddle Summary as an artefact

The output of a Swarm-Lite session is a saved, versioned document — not a conversation thread. A Huddle Summary is a document with a title, a date, a composite recommendation, per-persona sections, and a list of Pending Actions. It can be shared with a stakeholder who was not in the session. It can be retrieved six months later when a similar question arises.

The connection to TX-1 and SS-1

TX-1 acts on failures inside your systems. SS-1 monitors for changes outside them. Swarm-Lite simulates how your users will react before you make the change.

Together they complete the full decision loop: detect what is broken, monitor what is changing, simulate how users will respond, then act. All three systems share one interaction model — something changes, an agent reasons about it, a human approves the response — because the underlying problem is the same problem viewed from three different angles.

What this demonstrates

A multi-agent orchestration system where personas are typed entities, not prompt fragments. An artefact-first research model where the output is a document, not a transcript. A HITL approval pattern applied to strategic decisions, not just operational ones.

Status and direction

Swarm-Lite demo is complete. Active development continues on the Huddle orchestration depth, the persona auto-generation pipeline, and the integration layer that connects Swarm-Lite simulation output to SS-1 market monitoring.